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ICANN
2001
Springer
14 years 15 hour ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
PAMI
2006
128views more  PAMI 2006»
13 years 7 months ago
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
A new approach to support vector machine (SVM) classification is proposed wherein each of two data sets are proximal to one of two distinct planes that are not parallel to each oth...
Olvi L. Mangasarian, Edward W. Wild
VISUALIZATION
1997
IEEE
13 years 11 months ago
Fast oriented line integral convolution for vector field visualization via the Internet
Oriented Line Integral Convolution (OLIC) illustrates flow fields by convolving a sparse texture with an anisotropic convolution kernel. The kernel is aligned to the underlying ...
Rainer Wegenkittl, Eduard Gröller
CVPR
2010
IEEE
13 years 10 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
ICANN
2007
Springer
13 years 11 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel